Skill UI

This skill functions as an expert in workflow automation, specializing in designing and implementing robust CI/CD pipelines and GitHub Actions workflows. It guides users through automating the entire development lifecycle—from building and testing to secure deployment. By establishing clear stages, handling secrets, and defining rollback strategies, it ensures consistency, reduces manual effort, and accelerates delivery while maintaining high quality and security standards.

This guide details security best practices for integrating with Clay. It covers securing API keys, validating webhook signatures, isolating provider credentials, and redacting sensitive PII data. Essential for maintaining compliance and data integrity in production environments.

A comprehensive guide for engineering teams to manage critical incidents related to Clerk authentication and SaaS platform outages. It covers full incident lifecycle procedures, including initial triage, emergency auth bypass implementation, key rotation, session recovery scripts, and post-incident root cause analysis. Use this when facing production authentication failures or security breaches.

Automates cloud security posture assistance within the Security Advanced domain, guiding practitioners through best practices, compliance checks, threat modeling, and prod-ready configurations whenever they mention cloud security posture.

An expert AI specialist that integrates advanced static analysis (e.g., CodeQL, SonarQube) with modern DevOps practices. It performs multi-layered code reviews, checking for security vulnerabilities, performance bottlenecks, architectural flaws, and adherence to best practices across various languages. Ideal for CI/CD pipelines and pull request validation.

This comprehensive checklist provides a systematic framework for conducting thorough code reviews. It covers critical areas including functionality, security vulnerabilities, performance optimization, and overall code maintainability. Use it when reviewing pull requests, conducting code audits, or standardizing team development practices.

This skill helps transform code reviews from simple gatekeeping into a powerful knowledge-sharing mechanism. It guides users through systematic analysis of code changes, focusing on correctness, security, performance, and maintainability. Use it when reviewing pull requests, establishing best practices, or mentoring developers to ensure high-quality, robust codebase development.

This skill functions as a dedicated dependency security expert, specializing in auditing project dependencies. It analyzes codebases for known security vulnerabilities, license compliance issues, outdated packages, and overall supply chain risks. It provides comprehensive, actionable remediation strategies and detailed risk reports to keep software supply chains secure and compliant.

Automates CodeQL database builds, suite selection, and taint-aware scans to surface security and quality issues across supported languages, handling output directories, SARIF results, and extensions in one workflow.

This skill executes CodeRabbit's core workflow, providing automated, in-depth code reviews directly on pull requests. It analyzes code diffs based on custom rules (e.g., API validation, DB security), generates detailed walkthrough summaries, and posts line-level feedback. Ideal for setting up robust CI/CD quality gates and maintaining high code standards throughout the development lifecycle.

This skill guides users on fine-tuning CodeRabbit's review quality. It teaches the AI agent team preferences through PR feedback, integrates custom code guidelines (e.g., security policies), allows customization of the review tone, and implements path filters to drastically reduce false positives and noise. This ensures that all code feedback is highly relevant, actionable, and aligns with specific team standards.

This skill guides the comprehensive, multi-step rollout of CodeRabbit AI code review across an entire organization. It covers setting organization-level defaults, customizing team-specific review rules (e.g., API security, frontend performance), and automating deployment via multi-repo scripts and branch protection enforcement. Use when establishing standardized, high-quality AI code review practices company-wide.